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It is estimated that 1 billion waste tires are generated every year across the globe, yet only 10% are being processed, and much rubber waste is yielded during manufacturing. These waste tires and rubber scraps are poisonous to the environment when processed via incineration and landfill. Rubber circular manufacturing is an effective solution that reduces not only rubber waste but also raw material costs. In this paper we propose a two-line flowshop model for the circular rubber manufacturing problem (CRMP), where the job sequence of two production lines is appropriately aligned to obtain the shortest makespan while guaranteeing that sufficient rubber waste yielded in the first line is ready to be reused for circular production in the second line. A genetic algorithm (GA) is developed, and the design of its genetic operations is customized to the CRMP context to achieve efficient and effective evolution. The experimental results with both real and synthetic datasets show that the GA significantly surpasses two heuristics in the literature by delivering the minimum makespan, which is 3.4 to 11.2% shorter than those obtained by the two competing methods.
Peng-Yeng Yin; Hsin-Min Chen; Yi-Lung Cheng; Ying-Chieh Wei; Ya-Lin Huang; Rong-Fuh Day. Minimizing the Makespan in Flowshop Scheduling for Sustainable Rubber Circular Manufacturing. Sustainability 2021, 13, 2576 .
AMA StylePeng-Yeng Yin, Hsin-Min Chen, Yi-Lung Cheng, Ying-Chieh Wei, Ya-Lin Huang, Rong-Fuh Day. Minimizing the Makespan in Flowshop Scheduling for Sustainable Rubber Circular Manufacturing. Sustainability. 2021; 13 (5):2576.
Chicago/Turabian StylePeng-Yeng Yin; Hsin-Min Chen; Yi-Lung Cheng; Ying-Chieh Wei; Ya-Lin Huang; Rong-Fuh Day. 2021. "Minimizing the Makespan in Flowshop Scheduling for Sustainable Rubber Circular Manufacturing." Sustainability 13, no. 5: 2576.
Recently, two evolutionary algorithms (EAs), the glowworm swarm optimization (GSO) and the firefly algorithm (FA), have been proposed. The two algorithms were inspired by the bioluminescence process that enables the light-mediated swarming behavior for mating or foraging. From our literature survey, we are convinced with much evidence that the EAs can be more effective if appropriate responsive strategies contained in the adaptive memory programming (AMP) domain are considered in the execution. This paper contemplates this line and proposes the Cyber Firefly Algorithm (CFA), which integrates key elements of the GSO and the FA and further proliferates the advantages by featuring the AMP-responsive strategies including multiple guiding solutions, pattern search, multi-start search, swarm rebuilding, and the objective landscape analysis. The robustness of the CFA has been compared against the GSO, FA, and several state-of-the-art metaheuristic methods. The experimental result based on intensive statistical analyses showed that the CFA performs better than the other algorithms for global optimization of benchmark functions.
Peng-Yeng Yin; Po-Yen Chen; Ying-Chieh Wei; Rong-Fuh Day. Cyber Firefly Algorithm Based on Adaptive Memory Programming for Global Optimization. Applied Sciences 2020, 10, 8961 .
AMA StylePeng-Yeng Yin, Po-Yen Chen, Ying-Chieh Wei, Rong-Fuh Day. Cyber Firefly Algorithm Based on Adaptive Memory Programming for Global Optimization. Applied Sciences. 2020; 10 (24):8961.
Chicago/Turabian StylePeng-Yeng Yin; Po-Yen Chen; Ying-Chieh Wei; Rong-Fuh Day. 2020. "Cyber Firefly Algorithm Based on Adaptive Memory Programming for Global Optimization." Applied Sciences 10, no. 24: 8961.
The phenomenon of banner blindness has concerned researchers, advertisers and website publishers during these years. In order to alleviate the phenomenon, this study attempted to develop a banner recommendation system which could arrange banners according the relative salience of keywords on a webpage viewed by a user. The prototypical system are being developed, however, we have made an initial examination on the effectiveness of its banner recommendation functionality. It was found that two recommendation accuracies for the system calculated with two different criteria both were significantly higher than the probability by chance.
Rong-Fuh Day; Chien-Ying Chou. Examining the Validity of the Banner Recommendation System. Transactions on Petri Nets and Other Models of Concurrency XV 2015, 317 -324.
AMA StyleRong-Fuh Day, Chien-Ying Chou. Examining the Validity of the Banner Recommendation System. Transactions on Petri Nets and Other Models of Concurrency XV. 2015; ():317-324.
Chicago/Turabian StyleRong-Fuh Day; Chien-Ying Chou. 2015. "Examining the Validity of the Banner Recommendation System." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 317-324.